Skip navigation
Please use this identifier to cite or link to this item:
Title: MultiChannel Pattern Analysis: Correlation-Based Decoding with fNIRS
Contributors: Emberson, Lauren
Zinszer, Benjamin
Issue Date: 7-Oct-2016
Description: Implement multichannel pattern analysis (MCPA) with NIRS a la Emberson, Zinszer, Raizada and Aslin If you want to be alerted of updates to the code, please email Benjamin Zinszer You will only receive emails if there are significant changes made to the code. Alternatively, come back and visit this github repository because changes will be pushed to this location. Two datasets were used in the paper. Dataset #1 has been published in Emberson, Richards & Aslin (2015, control group) and is available in full as part of this repository. Dataset #2 has yet to be published and thus the original dataset is not yet available in this repository. The output of this code (i.e., decoding accuracy) is available for both datasets, along with the code used for implementing the mixed effects models reported in Emberson, Zinszer, Raizada and Aslin is available in a complementary repository If you have questions, please email either Lauren Emberson or Benjamin Zinszer
Appears in Collections:Research Data Sets

Files in This Item:
File Description SizeFormat 
ReadME.txt1.08 kBTextView/Download
LICENSE17.62 kBUnknownView/Download
allData_MultiRS2_struct.mat323.25 MBUnknownView/Download
estimate_WindowAverages.m3.91 kBUnknownView/Download
get_subject_events2.m1.63 kBUnknownView/Download
leave_one_Ss_out_classifyAverages.m10.15 kBUnknownView/Download
leave_one_Ss_out_classifyIndividualEvents.m13.52 kBUnknownView/Download
SampleAnalysesForDataset1.m1.94 kBUnknownView/Download
WDIT_control2_Ss1_25_homerandotp.mat427.21 MBUnknownView/Download

Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.